Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
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There is a need for valid self-report measures of core health-related quality of life (HRQoL) domains. ⋯ Although these profile measures have been used widely, with summary scoring routines published, description of their development, reliability, and initial validity has not been published until this article. Further evaluation of these measures and clinical applications are encouraged.
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This paper examines the implications of the improvements in observational methods and research design, as well as the growing availability of real world data for the quality of RWE. These developments have been very positive. On the other hand, unstructured data, such as medical notes, and the sparcity of data created by merging multiple data assets are not easily handled by traditional health services research statistical methods. In response, machine learning methods are gaining increased traction as potential tools for analyzing massive, complex datasets. ⋯ Machine learning methods have traditionally been used for classification and prediction, rather than causal inference. The prediction capabilities of machine learning are valuable by themselves. However, using machine learning for causal inference is still evolving. Machine learning can be used for hypothesis generation, followed by the application of traditional causal methods. But relatively recent developments, such as targeted maximum likelihood methods, are directly integrating machine learning with causal inference.
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The APHINITY trial assessed the effectiveness and the safety of adding pertuzumab to trastuzumab and chemotherapy (THP) compared to trastuzumab and chemotherapy (TH) in the adjuvant management of human epidermal growth factor 2-positive (HER2+) breast cancer. We performed a study to project the potential cost-effectiveness of THP vs. TH. ⋯ The addition of pertuzumab to the available regimens for HER2+ early breast cancer is likely to be cost-effective for patients in the U.S. at high risk of recurrence.
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Opioid abuse is a significant public health problem in the United States. We evaluate the clinical effectiveness and economic impact of abuse-deterrent formulations (ADF) of opioids relative to non-ADF opioids in preventing abuse. ⋯ ADF opioids have the potential to prevent new cases of opioid abuse, but at substantially higher costs to the health system.
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To evaluate the cost-effectiveness of financial incentives for human immunodeficiency virus (HIV) viral suppression compared to standard of care. ⋯ Financial incentives, as used in HTPN 065, are estimated to improve quality and length of life, reduce HIV transmissions, and save money from a societal perspective. Financial incentives offer a promising option for enhancing the benefits of medication in the United States.